Systems and methods for utilizing telematics data to improve fleet management operations

ABSTRACT

According to various embodiments, a fleet management system is provided for capturing, storing, and analyzing telematics data to improve fleet management operations. The fleet management system may be used, for example, by a shipping entity (e.g., a common carrier) to capture telematics data from a plurality of vehicle sensors located on various delivery vehicles and to analyze the captured telematics data. In particular, various embodiments of the fleet management system are configured to analyze engine idle data in relation to other telematics data in order to identify inefficiencies, safety hazards, and theft hazards in a driver&#39;s delivery process. The fleet management system may also be configured to assess various aspects of vehicle performance, such as vehicle travel delays and vehicle speeds. These analytical capabilities allow the fleet management system to assist fleet managing entities, or other entities, in analyzing driver performance, reducing fuel and maintenance costs, and improving route planning.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of U.S. Nonprovisional Application Ser. No. 14/517,500, filed Oct. 17, 2014, which is a continuation of U.S. Nonprovisional application Ser. No. 13/799,627 filed Mar. 13, 2013 and now issued as U.S. Pat. No. 8,896,430, which is a continuation of U.S. Nonprovisional application Ser. No. 12/556,140 filed Sep. 9, 2009 and now issued as U.S. Pat. No. 8,416,067, which claims the benefit of U.S. Provisional Application No. 61/095,486, filed Sep. 9, 2008, each of which is herein incorporated by reference in its entirety.

BACKGROUND

Delivery vehicle driver efficiency, avoidance of safety and theft hazards, and optimization of route planning are objectives for transportation companies. Accordingly, there is an ongoing need to develop new technologies to enhance driver efficiency, the avoidance of safety and theft hazards, and route planning.

BRIEF SUMMARY

According to various embodiments of the present invention, a fleet management system is provided for capturing, storing, and analyzing telematics data to improve fleet management operations. Various embodiments of the fleet management system include one or more memory storage areas and one or more processors, wherein the fleet management system is configured to (i) receive telematics data from one or more vehicle sensors associated with a vehicle, the telematics data comprising engine idle data relating to the engine idle time of the vehicle; (ii) associate the telematics data with a particular segment of a vehicle trip; and (iii) execute a step selected from a group consisting of: (a) determining whether the telematics data indicates a potential inefficient operation by a driver of the vehicle and, in response to determining that the telematics data indicates a potential inefficient operation by the driver, generating an alert indicating the potential inefficient operation; (b) determining whether the telematics data indicates a potential safety hazard created by a driver of the vehicle and, in response to determining that the telematics data indicates a potential safety hazard created by the driver, generating an alert indicating the potential safety hazard; and (c) determining whether the telematics data indicates a potential theft hazard created by a driver of the vehicle and, in response to determining that the telematics data indicates a potential theft hazard created by the driver, generating an alert indicating the potential theft hazard.

In another embodiment, the fleet management system includes (a) a fleet of vehicles having one or more vehicle sensors and at least one telematics device; (b) at least one computer network; (c) one or more central servers; and (d) a user interface; wherein the telematics device is configured to: receive telematics data from the one or more vehicle sensors, wherein the telematics data comprises data relating to the engine idle time of the fleet of vehicles; associate the telematics data with contextual data; and transmit the telematics data over the network to the central server; wherein the one or more central servers are configured to: (i) receive telematics data from the telematics device; (ii) execute the steps of: (a) determining whether the telematics data indicates a potential inefficient operation by a driver of the vehicle and, in response to determining that the telematics data indicates a potential inefficient operation by the driver, displaying via the user interface data indicating the potential inefficient operation; (b) determining whether the telematics data indicates a potential safety hazard created by a driver of the vehicle and, in response to determining that the telematics data indicates a potential safety hazard created by the driver, displaying via the user interface data indicating the potential safety hazard; or (c) determining whether the telematics data indicates a potential theft hazard created by a driver of the vehicle and, in response to determining that the telematics data indicates a potential theft hazard created by the driver, displaying via the user interface data indicating the potential theft hazard.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Having thus described embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:

FIG. 1 is a block diagram of an exemplary fleet management system according to various embodiments;

FIG. 2 is a block diagram of a telematics device according to various embodiments of the present invention;

FIG. 3 is a schematic block diagram of a central server according to various embodiments;

FIG. 4 is a flow diagram of steps executed by the telematics device according to one embodiment;

FIG. 5 is a flow diagram of steps executed by the central server according to one embodiment;

FIG. 6 is a flow diagram of steps executed by the efficiency analysis module shown in FIG. 3 according to one embodiment;

FIG. 7 is a flow diagram of steps executed by the safety analysis module shown in FIG. 3 according to a particular embodiment;

FIG. 8 is a flow diagram of steps executed by the theft analysis module shown in FIG. 3 according to a certain embodiment;

FIG. 9 is a flow diagram of steps executed by the travel analysis module shown in FIG. 3 according to one embodiment; and

FIG. 10 is an exemplary user interface according to one embodiment.

DETAILED DESCRIPTION

Embodiments of the present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the inventions are shown. Indeed, embodiments of the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.

Overview

According to various embodiments of the present invention, a fleet management system is provided for capturing, storing, and analyzing telematics data to improve fleet management operations. The fleet management system may be used, for example, by a shipping entity (e.g., a common carrier, such as United Parcel Service, Inc., FedEx Corp., or the United States Postal Service) to capture telematics data from a plurality of vehicle sensors located on various delivery vehicles and to analyze the captured telematics data. In particular, various embodiments of the fleet management system are configured to analyze engine idle data in relation to other telematics data in order to identify inefficiencies, safety hazards, and theft hazards in a driver's delivery process. In addition, the fleet management system may be configured to assess various aspects of vehicle performance on specific shipping routes, such as vehicle travel delays and vehicle speeds. These analytical capabilities allow the fleet management system to assist shipping entities, other fleet managing entities, or other entities in analyzing driver performance, reducing fuel and maintenance costs, and improving route planning.

For example, an exemplary fleet management system includes various delivery vehicles having a variety of vehicle sensors. The vehicle sensors are configured to measure various conditions related to the vehicle (e.g., engine ignition, engine speed, vehicle speed, seat belt status, vehicle heading, and vehicle location). The sensors are controlled by a telematics device configured to capture and store telematics data (e.g., engine idle data) when certain defined vehicle events are detected.

Telematics data is captured by the fleet management system from the vehicles in the fleet as they execute various delivery routes. For the purposes of the fleet management system, each delivery route is comprised of a series of vehicle trips. A vehicle trip comprises starting the vehicle's engine, traveling some distance, and turning off the vehicle's engine. For example, when a driver starts a delivery vehicle to travel to a destination, a vehicle trip begins. When the driver reaches the destination and shuts off the engine while delivering the package, the vehicle trip ends. Thus, a full delivery route will often comprise a number of vehicle trips. Each vehicle trip may be further divided into a Start of Trip segment (e.g., the time period between vehicle's engine turning on and the vehicle beginning to travel to its destination), a During Travel segment (e.g., the period of time during which the vehicle travels to its destination with the vehicle's engine on), and an End of Trip segment (e.g., the period of time between the vehicle stopping at its destination and the vehicle's engine turning off).

To analyze the efficiency of a driver, the fleet management system is configured to examine the telematics data received from the vehicle operated by the driver and to identify periods of engine idle time having an abnormally long duration. The system then examines other telematics data captured near in time to each period of engine idle time to determine the cause of the excessive idle time. For example, the system may recognize that a driver unnecessarily allowed the vehicle's engine to idle while he or she fastened a seat belt by identifying abnormally long engine idle period in a Start of Trip vehicle segment and identifying telematics data near that engine idle period indicating that the driver's seat belt was engaged. The system may then alert a user (e.g., the driver, the driver's manager, or a central vehicle monitor) of this inefficiency. The driver may then be instructed (e.g., in person, or via an electronic message generated by the system), to fasten their seatbelt before starting the vehicle's engine. By instructing the driver to fasten his or her seat belt before starting the vehicle's engine, a shipping entity user reduces fuel consumption and engine running time for the vehicle.

The system may employ similar logic to identify other potential inefficiencies, safety hazards, and theft hazards. In addition, as will be described in more detail below, the fleet management system is also configured to calculate various travel statistics (e.g., engine idle time percentage, average vehicle speed, and average travel delays) and provide efficiency comparison tools (e.g., comparing driver efficiencies and travel delays for routes).

Identifying inefficiencies within a driver's routine and practices allows fleet operators to correct these inefficient practices and reduce the amount of idle time for deliveries. Indeed, the excess engine idle time associated with inefficient driver practices results in fuel being wasted and engine running time being increased. When aggregated over a large fleet of vehicles, these inefficiencies may amount to significant fuel and maintenance costs. In addition, the travel statistics and comparison tools provided by the fleet management system allow users to optimize shipping routes and logistical planning.

System Architecture

A fleet management system 5 according to one embodiment is shown in FIG. 1. In the illustrated embodiment, the fleet management system 5 includes one or more delivery vehicles 100, a portable data acquisition device 110, and a central server 120. The one or more delivery vehicles 100 each include a plurality of vehicle sensors (not shown) and a telematics device 102. The telematics device 102, portable data acquisition device 110, and central server 120 are connected to communicate with each other via a communications network 130 (e.g., the Internet, an Intranet, or other suitable network). In addition, the telematics device 102, portable data acquisition device 110, and central server 120 are configured for storing data to an accessible database (not shown) that may be stored on (or, alternatively, stored remotely from) the central server 120.

In the illustrated embodiment, the delivery vehicles 100 are responsible for the pickup and delivery of a plurality of packages within a particular delivery area. Each delivery vehicle 100 includes a plurality of vehicle sensors included within, or associated with, each delivery vehicle 100. As is discussed in more detail below, the vehicle sensors generate telematics data associated with engine ignition, engine speed, vehicle speed, vehicle location, the status of vehicle seat belts, doors, and handles, and/or other aspects of the vehicle, the vehicles' various components and/or the environment in which the vehicle is operating.

The telematics device 102 is included within, or otherwise associated with, each delivery vehicle 100 for the purpose of controlling the vehicle sensors, capturing and storing telematics data from the vehicle sensors, and/or associating the captured telematics data with contextual data. The telematics device 102 may include, for example, a processor and memory that can collect and capture and/or transmit data from vehicle sensors. For example, the telematics device 102 may be a computing device (e.g., a PC, server, desktop, or a handheld computing device), a programmable logic controller (PLC), an active RFID tag, or other suitable device. The analysis of the data collected by the telematics device 102 may be performed by software or algorithms executed by the processor of the telematics device or by a processor of a computing device that receives the data collected by the telematics device 102.

The telematics device 102 is further configured to transmit data over the network 130 to the portable data acquisition device 110 and/or the central server 120. As discussed in more detail below in regard to FIGS. 5-9, in response to receiving the telematics data from the telematics device 102 and/or the portable data acquisition device 110, as well as data received from other systems or devices operating in connection with the overall fleet management system 5, the central server 120 is configured to analyze the received telematics data and identify data indicating various inefficiencies, safety hazards, or security hazards present in the deliveries carried out by one or more drivers of the delivery vehicles 100.

In one embodiment, the telematics device 102 transmits some or all of the telematics data, via any suitable wired or wireless communication network 130, to a portable data acquisition device 110 (e.g., cellular telephone, personal digital assistant (PDA), laptop, etc.) operated by a driver associated with the delivery vehicle 100. The portable data acquisition device 110 may, in turn, transmit, via the same or different communication network 130, some or all of the received data to a central server 120, or similar network entity or mainframe computer system. In addition, according to one embodiment, the telematics device 102 may further transmit some or all of the telematics data directly to the central server 120, via the same or different communication network 130.

According to embodiments of the present invention, the communication network 130 may be capable of supporting communication in accordance with any one or more of a number of second-generation (2G), 2.5G and/or third-generation (3G) mobile communication protocols or the like. More particularly, network 130 may be capable of supporting communication in accordance with 2G wireless communication protocols IS-136 (TDMA), GSM, and IS-95 (CDMA). Also, for example, the network 130 may be capable of supporting communication in accordance with 2.5G wireless communication protocols GPRS, Enhanced Data GSM Environment (EDGE), or the like. In addition, for example, the network 130 can be capable of supporting communication in accordance with 3G wireless communication protocols such as Universal Mobile Telephone System (UMTS) network employing Wideband Code Division Multiple Access (WCDMA) radio access technology. Some narrow-band AMPS (NAMPS), as well as TACS, network(s) may also benefit from embodiments of the present invention, as should dual or higher mode mobile stations (e.g., digital/analog or TDMA/CDMA/analog phones). As yet another example, the telematics device 102 and portable data acquisition device 110 may be configured to communicate with one another in accordance with techniques such as, for example, radio frequency (RF), Bluetooth™, infrared (IrDA), or any of a number of different wireless networking techniques, including Wireless LAN (WLAN) techniques.

Although the telematics device 102, portable data acquisition device 110, and central server 120 are illustrated in FIG. 1 as communicating with one another over the same network 130, these devices may likewise communicate over separate networks. For example, while the telematics device 102 may communicate with the portable data acquisition device 110 over a wireless personal area network (WPAN) using, for example, Bluetooth techniques, the telematics device 102 and/or portable data acquisition device 110 may communicate with the central server 120 over a wireless wide area network (WWAN), for example, in accordance with EDGE, or some other 2.5G wireless communication protocol.

According to one embodiment, in addition to receiving telematics data from the telematics device 102, the portable data acquisition device 110 may be further configured to collect and transmit telematics data on its own. For example, according to one embodiment, the portable data acquisition device 110 may include a location determining device, such as a Global Positioning System (GPS) device, for providing location information in the form of, for example, latitude and longitude values. In particular embodiments, and as is discussed in more detail below, this location determining device may be used to gather information regarding the location of the driver him- or herself, as opposed to location information associated with the delivery vehicle 100, which may be collected (or determined) by the telematics device 102.

The portable data acquisition device 110 may be any device associated with a carrier (e.g., UPS, FedEx, United States Postal Service (USPS), etc.). In various embodiments, the portable data acquisition device 110 may be capable of receiving data via one or more input units or devices, such as a keypad, touchpad, barcode scanner, radio frequency identification (RFID) reader, interface card (e.g., modem, etc.) or receiver. The portable data acquisition device 110 may further be capable of storing data to one or more volatile or non-volatile memory modules, and outputting the data via one or more output units or devices, for example, by displaying data to the user operating the device 110, or by transmitting data, for example over the communication network 130. One type of portable data acquisition device 110, which may be used in conjunction with embodiments of the present invention is the Delivery Information Acquisition Device (DIAD) presently utilized by UPS.

Vehicle Sensors

According to various embodiments, the delivery vehicles 100 are equipped with a variety of vehicle sensors. In certain embodiments, the delivery vehicles 100 include various combinations of sensors configured to make measurements pertaining to the following aspects of the delivery vehicles: engine ignition (e.g., on or off), engine speed (e.g., RPM and idle time events), vehicle speed (e.g., miles per hour), seat belt status (e.g., engaged or disengaged), vehicle heading (e.g., degrees from center), vehicle backing (e.g., moving in reverse or not moving in reverse), vehicle doors (e.g., open or closed), vehicle handles (e.g., grasped or not grasped by a driver), vehicle location (e.g., latitude and longitude), distance traveled (e.g., miles between two points), use of portable data acquisition device (e.g., in use or not in use), throttle position, brake pedal position, parking brake position, and other measurements (e.g., engine oil pressure, engine temperature, or engine faults).

According to various embodiments, on/off sensors, which register a voltage amount that corresponds with an on/off condition of a sensor, may be disposed within the vehicles 100 for collecting data. For example, in one embodiment, a seat belt sensor may register 0V when the seat belt is disengaged and 12V when the seat belt is engaged. This is sufficient for the seat belt sensor in particular because the seat belt is either engaged or disengaged at all times. As another example, one or more door position sensors may be connected, for example, to the driver side, passenger side, and bulkhead doors, and may register 0V when the door with which the sensor is associated is in an open position, and 12V when the door is closed. As another example, an ignition sensor may register 0V when the vehicle 100 is turned off and 12V when the vehicle 100 is turned on. As yet another example, a backing light sensor may register 0V when the vehicles' backing lights are off and 12V when the vehicle's backing lights are on. As yet another example, the engine idle sensor may be configured to generate 0V when the engine speed is above idle and 12V when the engine is idling.

According to various embodiments, variable voltage sensors, which may be used to register variations in voltage, may also be disposed within the delivery vehicles 100 for collecting data. For example, the engine speed sensor may detect the speed of the engine in revolutions per minute (RPM) by registering a particular voltage that corresponds to a particular RPM reading. The voltage of the sensor may increase or decrease proportionately with increases or decreases in the engine RPM. As another example, oil pressure sensors may detect the vehicle's oil pressure by registering a particular voltage that corresponds to a particular oil pressure. Other examples of variable voltage sensors may include temperature sensors, vehicle speed sensors, vehicle heading sensors, and vehicle location sensors.

The exemplary vehicle sensors described above may be configured, for example, to operate in any fashion suitable to generate computer-readable data that may be captured and transmitted by the telematics device 102. In addition, while certain sensors are preferably disposed at particular locations on or within the vehicle (e.g., handle sensors at the vehicle handles), certain sensors may be disposed anywhere within the vehicle, such as within the telematics device itself (e.g., location sensor).

Telematics Device

FIG. 2 provides a more detailed block diagram of an exemplary telematics device 102 in accordance with an embodiment of the present invention. As noted above and explained in greater detail below, the telematics device 102 may be configured to control a variety of vehicle sensors, collect vehicle telematics data generated by the sensors, and transmit the telematics data to the portable data acquisition device 110 and/or central server 120 via one of several communication methods.

In the illustrated embodiment, the telematics device 102 includes the following components: a processor 201, a location-determining device or sensor 202 (e.g., GPS sensor), a real-time clock 203, J-Bus protocol architecture 204, an electronic control module (ECM) 205, a port 206 for receiving data from vehicle sensors 410 in one of the delivery vehicles 100, a communication port 207 for receiving instruction data, a radio frequency identification (RFID) tag 305, a power source 208, a data radio 209 for communication with a WWAN, a WLAN and/or a WPAN, FLASH, DRAM, and NVRAM memory modules 303, and a programmable logic controller (PLC) 304. In an alternative embodiment, the RFID tag 305, the location sensor 202, and the PLC 304 may be located in the delivery vehicle 100 external to the telematics device 102. In various embodiments, the telematics device may omit certain of the components described above. It should be understood that the telematics device may include any other suitable components. For example, the telematics device may include other types of communications components than those described above.

According to one embodiment, the processor 201 is configured to capture and store telematics data from one or more vehicle sensors 410 on a delivery vehicle 100 upon the occurrence of one or more defined vehicle events. As is described in greater detail below, the processor 201 is configured such that any parameter measurable by the one or more vehicle sensors 410 may be defined as a vehicle event. In addition, the processor 201 may be configured to capture and store data from any one of, or any combination of, the vehicle sensors 410 in response to detecting a defined vehicle event. The processor 201 is also configured to associate telematics data received from the vehicle sensors 410 with contextual data indicating, for example: (1) the time the data was captured (e.g., through time-stamping), (2) the vehicle the data was captured from, (3) the driver of the vehicle, (4) a log reason for capturing the data, and/or (5) the route the driver was on at the time the data was collected. In various embodiments, the processor 201 is further configured to transmit the telematics data to the portable data acquisition device 110 and/or the central server 120. In other embodiments, the processes described herein as being carried out by a single processor may be accomplished by multiple processors.

In one embodiment, the location sensor 202, which may be one of several components available in the telematics device 102, may be compatible with a low Earth orbit (LEO) satellite system or a Department of Defense (DOD) satellite system. Alternatively, triangulation may be used in connection with various cellular towers positioned at various locations throughout a geographic area in order to determine the location of the delivery vehicle 100 and/or its driver. The location sensor 202 may be used to receive position, time, and speed data. It will be appreciated by those skilled in the art that more than one location sensor 202 may be utilized, and that other similar techniques may likewise be used to collect geo-location information associated with the delivery vehicle 100 and/or its driver.

In one embodiment, the ECM 205 with J-Bus protocol 204 may be one of several components available in the telematics device 102. The ECM 205, which may be a scalable and subservient device to the telematics device 102, may have data processor capability to decode and store analog and digital inputs and ECM data streams from vehicle systems and sensors 410, 420. The ECM 205 may further have data processing capability to collect and present vehicle data to the J-Bus 204 (which may allow transmittal to the telematics device 102), and output standard vehicle diagnostic codes when received from a vehicle's J-Bus-compatible on-board controllers 420 or vehicle sensors 410.

In one embodiment, an instruction data receiving port 207 may be one of several components available in the telematics device 102. Embodiments of the instruction data receiving port 207 may include an Infrared Data Association (IrDA) communication port, a data radio, and/or a serial port. The instruction receiving data port 207 may receive instructions for the telematics device 102. These instructions may be specific to the vehicle 100 in which the telematics device 102 is installed, specific to the geographical area in which the vehicle 100 will be traveling, or specific to the function the vehicle 100 serves within the fleet.

In one embodiment, a radio frequency identification (RFID) tag 305 may be one of several components available for use with the telematics device 102. One embodiment of the RFID tag 305 may include an active RFID tag, which comprises at least one of the following: (1) an internal clock; (2) a memory; (3) a microprocessor; and (4) at least one input interface for connecting with sensors located in the vehicle 100 or the telematics device 102. Another embodiment of the RFID tag 305 may be a passive RFID tag. One or more RFID tags 305 may be internal to the telematics device 102, wired to the telematics device 102, and/or proximate to the telematics device 102. Each RFID tag 305 may communicate wirelessly with RFID interrogators within a certain geographical range of each other. RFID interrogators may be located external to the vehicle 100 and/or within the portable data acquisition device 110 that can be carried in and out of the vehicle 100 by the vehicle operator.

In one embodiment, the data radio 209 may be one of several components available in the telematics device 102. The data radio 209 may be configured to communicate with a WWAN, WLAN, or WPAN, or any combination thereof. In one embodiment, a WPAN data radio provides connectivity between the telematics device 102 and peripheral devices used in close proximity to the vehicle 100, such as the portable data acquisition device 110, a local computer, and/or a cellular telephone. As mentioned above, in one embodiment of the invention, a WPAN, such as, for example, a Bluetooth™ network (IEEE 802.15.1 standard compatible) may be used to transfer information between the telematics device 102 and the portable data acquisition device 110. In other embodiments, WPANs compatible with the IEEE 802 family of standards may be used. In one embodiment, the data radio 209 may be a Bluetooth™ serial port adapter that communicates wirelessly via WPAN to a Bluetooth™ chipset located in the portable data acquisition device 110, or other peripheral device. As discussed above with regard to FIG. 1, and as one of ordinary skill in the art will readily recognize, other wireless protocols exist (e.g., cellular technology) and can likewise be used in association with embodiments of the present invention.

As discussed above with regard to FIG. 1, in one embodiment, vehicle performance and tracking data collected by the telematics device 102 (i.e., telematics data) may be transmitted via a WPAN to, and stored by, the portable data acquisition device 110 until a communication link can be established between the portable data acquisition device 110 and the central server 120, or similar network entity or mainframe computer system. In one embodiment, the portable data acquisition device 110 may display telematics data for the driver's viewing, which may be helpful in troubleshooting vehicle performance problems and showing delivery route progress and instructions. In an alternative embodiment, the portable data acquisition device 110 may be a hand-held data acquisition device, like an iPAQ. The Media Access Control (MAC) address, which is a code unique to each Bluetooth™-enabled device that identifies the device, similar to an Internet protocol address identifying a computer in communication with the Internet, can be communicated to other devices in communication with the WPAN, which may assist in identifying and allowing communication among vehicles, cargo, and portable data acquisition devices equipped with Bluetooth™ devices.

Central Server

In various embodiments, the central server includes various means for performing one or more functions in accordance with embodiments of the present invention, including those more particularly shown and described herein. It should be understood, however, that the central server may include alternative devices for performing one or more like functions, without departing from the spirit and scope of the present invention.

FIG. 5 is a schematic diagram of the central server 120 according to various embodiments. The central server 120 includes a processor 60 that communicates with other elements within the central server 120 via a system interface or bus 61. Also included in the central server 120 is a display device/input device 64 for receiving and displaying data. This display device/input device 64 may be, for example, a keyboard or pointing device that is used in combination with a monitor. The central server 120 further includes memory 66, which preferably includes both read only memory (ROM) 65 and random access memory (RAM) 67. The server's ROM 65 is used to store a basic input/output system 26 (BIOS), containing the basic routines that help to transfer information between elements within the central server 120.

In addition, the central server 120 includes at least one storage device 63, such as a hard disk drive, a floppy disk drive, a CD Rom drive, or optical disk drive, for storing information on various computer-readable media, such as a hard disk, a removable magnetic disk, or a CD-ROM disk. As will be appreciated by one of ordinary skill in the art, each of these storage devices 63 is connected to the system bus 61 by an appropriate interface. The storage devices 63 and their associated computer-readable media provide nonvolatile storage for a personal computer. It is important to note that the computer-readable media described above could be replaced by any other type of computer-readable media known in the art. Such media include, for example, magnetic cassettes, flash memory cards, digital video disks, and Bernoulli cartridges.

A number of program modules may be stored by the various storage devices and within RAM 65. Such program modules include an operating system 80, a efficiency analysis module 600, a safety analysis module 700, a theft analysis module 800, and a travel analysis module 900. According to various embodiments, the efficiency analysis module 500, safety analysis module 600, theft analysis module 700, and travel analysis module 900 control certain aspects of the operation of the central server 120 with the assistance of the processor 60 and operating system 80.

In general, the efficiency analysis module 600 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential inefficient operation of a delivery vehicle and (ii) identify specific inefficient operations indicated by the engine idle segments and associated telematics data. The safety analysis module 700 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential safety hazards present in the operation of a delivery vehicle and (ii) identify specific safety hazards indicated by the engine idle segments and associated telematics data. The theft analysis module 800 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential theft hazards present in the operation of a delivery vehicle and (ii) identify specific theft hazards indicated by the engine idle segments and associated telematics data. The travel analysis module 600 is configured to provide a user with various options for analyzing travel aspects of the delivery vehicles 100 in the fleet management system 5. Embodiments of these modules are described in more detail below in relation to FIGS. 6-9.

In a particular embodiment, these program modules 600, 700, 800, and 900, are executed by the central server 120 and are configured to generate graphical user interfaces accessible to users of the system. In one embodiment, the user interfaces may be accessible via the Internet or other communications network. In other embodiments, one or more of the modules 600, 700, 800, and 900 may be stored locally on one or more computers and executed by one or more processors of the computers. According to various embodiments, the modules 600, 700, 800, and 900 may send data to, receive data from, and utilize data contained in, a database, which may be comprised of one or more separate, linked databases.

Also located within the central server 120 is a network interface 74, for interfacing and communicating with other elements of a computer network. It will be appreciated by one of ordinary skill in the art that one or more of the central server 120 components may be located geographically remotely from other central server 120 components. Furthermore, one or more of the components may be combined, and additional components performing functions described herein may be included in the central server 120.

While the foregoing describes a single processor 60, as one of ordinary skill in the art will recognize, the central server 120 may comprise multiple processors operating in conjunction with one another to perform the functionality described herein. In addition to the memory 66, the processor 60 can also be connected to at least one interface or other means for displaying, transmitting and/or receiving data, content or the like. In this regard, the interface(s) can include at least one communication interface or other means for transmitting and/or receiving data, content or the like, as well as at least one user interface that can include a display and/or a user input interface. The user input interface, in turn, can comprise any of a number of devices allowing the entity to receive data from a user, such as a keypad, a touch display, a joystick or other input device.

While reference is made to a central “server” 120, as one of ordinary skill in the art will recognize, embodiments of the present invention are not limited to a client-server architecture. The system of embodiments of the present invention is further not limited to a single server, or similar network entity or mainframe computer system. Other similar architectures including one or more network entities operating in conjunction with one another to provide the functionality described herein may likewise be used without departing from the spirit and scope of embodiments of the present invention. For example, a mesh network of two or more personal computers (PCs), or similar electronic devices, collaborating with one another to provide the functionality described herein in association with the central server 120 may likewise be used without departing from the spirit and scope of embodiments of the present invention.

Telematics Device Configuration and Logic

As described above, in various embodiments, the telematics device is generally configured to control a variety of vehicle sensors, capture and store vehicle telematics data generated by the sensors, associate the collected telematics data with contextual data, and transmit the telematics data to the portable data acquisition device 110 and/or central server 120.

According to various embodiments, the processor 201 of the telematics device 102 is configured to capture and store telematics data from any one of, or any combination of, the vehicle sensors 410 in response to detecting a defined vehicle event. The processor 201 is configured such that any parameter measurable by the one or more vehicle sensors 410 may be defined as a vehicle event.

For example, in one embodiment, the processor 201 is configured such that vehicle events include (a) the engine of the vehicle 100 being turned on or off, (b) the engine of the vehicle 100 beginning to idle or ceasing to idle, and (c) a seat belt in the vehicle being engaged or disengaged. In this embodiment, the processor 201 is also configured to instantaneously capture data from certain vehicle sensors 410 upon the occurrence of any vehicle event. Accordingly, in one embodiment, the processor 201 will capture and store data from all vehicle sensors 410 any time one of the vehicle events (a), (b), or (c) is detected by any of the vehicle sensors 410.

In this embodiment, if the vehicle's engine is on and the vehicle speed becomes zero (e.g., the vehicle begins to idle), the telematics device 102 will capture and store data from a predetermined set of vehicle sensors 410 (e.g., the vehicle's engine speed sensor, speed sensor, seat belt status sensor, direction sensor, and location sensor). In addition, if the vehicle is idling, another vehicle event will be detected when the vehicle increases its speed above zero or the engine turns off. As a result, in this embodiment, vehicle events are detected and telematics data is captured and stored at the beginning and end of every period during which the vehicle's engine is idling. This ensures that the telematics device 102 captures every period of engine idling for each delivery vehicle.

According to various embodiments, the processor 201 may also be configured to define vehicle events through the varying parameters measured by certain vehicle sensors 410. For example, in one embodiment, the processor 201 is configured such that a vehicle event is detected anytime the vehicle's heading is greater than a predetermined number of degrees (e.g., about 5 degrees) from center to the left or right (e.g., the driver turns the steering wheel such that the vehicle is heading 10 degrees to the right). However, in another embodiment, the processor 201 is configured such that a vehicle event is also detected when the vehicle turns 10 degrees or more. This principle may be applied to other vehicle sensors capable of measuring variable parameters (e.g., RPM as measured by an engine speed sensor or miles per hour as measured by a vehicle speed sensor).

According to various embodiments, the processor 201 may be configured to capture and store telematics data from any one of, or any combination of, the vehicle sensors 410 in response to detecting a defined vehicle event. As described above, in one embodiment, the processor 201 is configured to capture and store telematics data from a predefined group of vehicle sensors 410 when a vehicle event is detected. For example, in one embodiment, the processor 201 is configured to capture and store data from only the seat belt sensor, engine speed sensor, and location sensor upon the occurrence of any specified vehicle event.

In other embodiments, the processor 201 may be configured to capture and store telematics data from certain vehicle sensors upon the occurrence of certain vehicle events. For example, in one embodiment, the processor 201 is configured such that (a) the seat belt being engaged or disengaged and (b) the vehicle moving in reverse are vehicle events. In this embodiment, the processor 201 is further configured to capture and store data from the seat belt sensor, engine speed sensor, and location sensor upon the occurrence of vehicle event (a) (i.e., the seat belt being engaged or disengaged), and to capture and store data from the vehicle speed sensor and location sensor upon the occurrence of vehicle event (b) (i.e., the vehicle moving in reverse).

The processor 201 may also be configured to capture and store telematics data from different vehicle sensors 410 upon the detection of certain values for vehicle events having varying parameters. For example, in one embodiment, the processor 201 is configured to capture and store telematics data from certain vehicle sensors when (a) the vehicle turns 5 degrees or more, while data will be captured from additional vehicle sensors when (b) the vehicle turns 10 degrees or more. This principle may be applied to other vehicle sensors capable of measuring variable parameters (e.g., RPM as measured by an engine speed sensor or miles per hour as measured by a vehicle speed sensor).

In further embodiments, the processor 201 may be configured to capture and store telematics data from certain vehicle sensors at certain time intervals if no vehicle events occur for a certain period of time. For example, in one embodiment, the processor 201 is configured such that, if no vehicle events are detected for 200 seconds, it will capture and store telematics data from certain (or all) vehicle sensors. In this embodiment, no more than 200 seconds of time will pass at any given point without data being collected from the vehicle sensors.

As described above, according to various embodiments, the processor 201 is also configured to associate telematics data received from the vehicle sensors 410 with contextual data including, but not limited to, data indicating the time the telematics data was captured (e.g., time-stamping), the vehicle the data was captured from, the driver of the vehicle, the route the driver was on at the time the data was collected, a log reason the data was captured, and/or the sensor the data was collected from. By associating and storing (e.g., in a database) the telematics data received from various vehicle sensors with this contextual data, the telematics device 102, central server 120, or other components of the fleet management system are able to search and identify stored telematics data for a particular date, time, vehicle, driver, sensed aspect of a vehicle, and/or route.

According to various embodiments, the defined vehicle events that trigger the telematics device to capture and store telematics data, the sensors from which telematics data are captured and stored in response to detected vehicle events, and the intervals defined for capturing and storing data when no vehicle events are detected each impact the effectiveness with which the fleet management system 5 identifies potential inefficiencies, safety hazards, and theft hazards present in a driver's routine and further analyzes the telematics data. For example, capturing data for a large amount of vehicle sensors at a high frequency may allow the fleet management system 5 to analyze the telematics data with greater accuracy. This could be accomplished, for example, by a fleet management system with many defined vehicle events and short intervals for capturing data if no vehicle events are detected.

However, as particular embodiments of the fleet management system 5 will have more limited storage space available to store telematics data, the amount of telematics data collected may be regulated. Accordingly, the telematics device 102 may be flexibly configured to suit the needs of a particular user. For example, a fleet management entity with limited data storage resources that is particularly interested in monitoring seat belt usage in a fleet of vehicles may configure the telematics devices of those vehicles to capture and store data from only those sensors relevant to seat belt status and capture data at the minimal frequency necessary to accurately report seat belt usage. This embodiment uses a small number of vehicle events and long time interval for capturing telematics data when no vehicle events are detected. As a contrasting example, a large fleet management entity with large amounts of data storage resources may configure the telematics devices of its large fleet of vehicles to capture and store data from a wide variety of vehicle sensors at a high frequency such that the telematics data may be analyzed to assess a wide variety of vehicle and driver efficiencies. As described above, this embodiment uses a large number of vehicle events and short time interval for capturing telematics data when no vehicle event is detected.

FIG. 4 illustrates exemplary steps executed by the telematics device 102 in controlling vehicle sensors, capturing and storing telematics data generated by the vehicle sensors, associating the collected telematics data with contextual information, and transmitting the telematics data to the portable data acquisition device 110 and/or central server 120. In the illustrated embodiment, the telematics device 102 has been configured to capture and store telematics data from certain sensors when the defined vehicle events with which they are associated are detected.

Beginning with step 402, the telematics device 102 continuously monitors readings from various vehicle sensors for parameters that match defined vehicle events. For example, in one embodiment, the telematics device 102 may monitor, among other sensors, the engine speed sensor and vehicle speed sensor to determine whether the vehicle's engine is idling. Next, at step 404, the telematics device 102 determines whether any of the defined vehicle events have occurred. If a vehicle event is not detected, the telematics device 102 moves back to step 402 and continues monitoring the vehicle sensors. If a vehicle event is detected, the telematics device 102 proceeds to step 406.

Next, at step 406, the telematics device 102 captures and stores data from the vehicle sensors associated with the vehicle event or vehicle events detected in step 404. For example, in one embodiment, the telematics device 102 is configured to capture the sensed telematics data at the instant a vehicle event is detected. In addition, according to one embodiment, the captured telematics data may be stored in the memory modules 303 of the telematics device 102 or in an associated database.

Next, at step 410, the telematics device 102 associates the telematics data captured and stored in step 406 with contextual data. In one embodiment, the contextual data indicates the date, time, vehicle, driver, route, and data type (e.g., the sensor that collected the data) for each captured piece of telematics data. For example, in step 406 the telematics device may capture the vehicle's engine speed in response to a vehicle event. The telematics data received from the vehicle sensor may be “1000 RPM,” indicating that the engine was turning at 1000 revolutions per minute when the telematics data was captured. In response, the telematics device 102 may associate the following exemplary contextual data: Date=/08/24/09; Time=12:36 PM; Vehicle=GA12345; Driver=Doe, John A.; Route=#61256; Data Type=Engine Speed. According to various embodiments, the contextual data may be any computer-readable and transmittable data format. For example, in one embodiment, the contextual data is metadata.

Next, at step 412, the telematics device 102 transmits the stored telematics data and associated contextual data to the central server 120. This may be accomplished by using any of the transmission methods and systems described herein. In another embodiment, the telematics device 102 is configured to transmit the telematics data and contextual data to the portable data acquisition device 110, rather than or in addition to, transmitting the data to the central server 120.

Central Server Logic

FIG. 5 illustrates exemplary steps executed by the central server 120 to analyze telematics data captured and stored by the telematics device 102, identify data indicating potential inefficiencies, safety hazards, and/or theft hazards, and provide a variety of travel analysis options for fleet managing entities. Beginning with step 502, the central server 502 monitors whether telematics data has been received from the telematics device 102 or portable data acquisition device 110. If telematics data is not being received from either device, the central server 120 moves to step 520. If the central server 120 determines that telematics data is being received from either device, the central server 120 moves to step 504. Next, at step 504, the central server 120 stores, in the system's memory, the telematics data and any associated contextual data received from the telematics device 102 or portable data acquisition device 110.

Next, at step 506, the central server 120 identifies any engine idle segments indicated by the received telematics data. The telematics data may contain data indicating engine idle events (e.g., telematics data indicating that a delivery vehicle's engine was on and the vehicle's speed was zero at a particular point in time). In the illustrated embodiment, the central server 120 is configured to identify strings of consecutive engine idle events comprising engine idle segments (which are described in more detail below).

Telematics data captured in response to a variety of vehicle events may indicate an engine idle event. For example, in one embodiment, the telematics device may be configured such that defined vehicle events include (a) a vehicle's engine beginning to idle, (b) a vehicle's engine ceasing to idle, and (c) a seat belt being fastened, and telematics data from an engine speed sensor and a seat belt sensor will be captured upon the occurrence of either event. In this embodiment, if a vehicle's engine begins to idle, a vehicle event will be detected and telematics data will be captured. The captured telematics data will indicate an engine idle event as the engine was idling the moment the data was captured. In addition, if a driver fastens a seat belt, another vehicle event will be detected and telematics data will again be captured. If the vehicle's engine was still idling, the captured telematics will indicate an additional engine idle event as the engine was idling when the telematics data was captured.

An engine idle segment represents a period of time during which a vehicle was idling, beginning when the vehicle starts to idle and ending when the vehicle stops idling. For example, in the embodiment described immediately above, if a vehicle traveling at speed encounters traffic and has to slow to a stop, a vehicle event will be detected the moment the vehicle's speed reaches zero while the vehicle's engine is running. When this vehicle event is detected, telematics data is captured and stored from the associated vehicle sensors. The telematics data captured in this instance will indicate an engine idle event. While the vehicle is idling in traffic, other vehicle events may be detected (e.g., the driver unfastens the seat belt) and additional telematics data may be captured. As described above, this telematics data will also indicate an engine idle event or events. As the vehicle accelerates, another vehicle event is detected when the vehicle's speed increases above zero and additional telematics data is captured and stored. The telematics data captured in this instance will also indicate an engine idle event. The string of engine idle events (e.g., the engine idle event indicated from the data captured when the vehicle began to idle, engine idle events indicated from the data captured while the vehicle remained idling, and the engine idle event indicated from the data captured when the vehicle ceased to idle) form an engine idle segment representing the period of time during which the vehicle was stopped in traffic and its engine was idling. By identifying each engine idle segment, the central server 120 determines the specific periods of time during which a vehicle's engine was idling.

Next, at step 508, the central server 120 associates the identified engine idle segments with a particular segment of a vehicle trip. This is accomplished by comparing the engine idle segments to telematics data indicating various vehicle events occurring before and after each engine idle segment.

As described above, in one embodiment, a vehicle trip may be divided into a Start of Trip segment, a During Travel segment, and an End of Trip segment. In one embodiment, the central server 120 associates each identified engine idle segment with a vehicle trip segment according to the following logic: (i) engine idle segments preceded by an engine off event (e.g., the engine simply being off) and followed by a travel event (e.g., the engine turned on and the vehicle moving) or another engine off event are associated with the Start of Trip Segment; (ii) engine idle segments preceded by a travel event and followed by another travel event are associated with the During Travel Segment; and (iii) engine idle segments preceded a travel event and followed by an engine off event are associated with the End of Trip Segment. As will be discussed in more detail below, FIG. 10 shows an exemplary user interface configured to display, among other things, a table of engine idle segments indicating the vehicle trip segment in which each engine idle segment occurred.

Next, at step 510, the central server 120 determines whether any of the identified engine idle segments have a statistically abnormal duration. In one embodiment, this determination is made by determining whether the duration of each engine idle segment exceeds an idle duration threshold for the vehicle trip segment with which the engine idle segment is associated. For example, a user of the fleet management system 5 may define an idle duration threshold for each vehicle trip segment. The target idle duration for Start of Trip events may be slightly longer than the target duration for End of Trip events due to the additional safety procedures a driver may go through after starting the engine, but before moving the vehicle (e.g., looking left, right, and in the mirrors to ensure it is safe to enter traffic).

A user of the fleet management system 5 may also specify parameters controlling which engine idle segments are identified by the central server 120 as having an abnormal duration. For example, in one embodiment, the user may specify that the central server 120 will identify all engine idle segments having a duration more than 5 seconds longer than their associated target idle duration. In another embodiment, where a user wants to identify only large idle periods, the user may specify that the central server 120 will identify all engine idle segments having a duration more than 20 seconds longer than their associated target idle duration. Accordingly, in one embodiment, at step 510, the central server 120 compares the duration of each engine idle segment to its relevant target duration and identifies all engine idle segments having a duration exceeding their target duration by an amount greater than or equal to a defined threshold value (e.g., a value specified by the user as described above).

If the central server 120 does not identify any engine idle segments having an abnormal duration, the central server 120 moves to step 516. If the central server 120 does identify one or more engine idle segments having an abnormal duration, the central server 120 moves to step 512. At step 512, the central server 120 assigns an alert identifier to the engine idle segments identified as having abnormal durations. For example, in one embodiment, the assigned alert identifiers are metadata identifying particular engine idle segments as having abnormal duration.

Next, at step 514, the central server generates an alert indicating to a user of the fleet management system 5 that engine idle data indicating at least one idle time of an abnormally long duration has been detected. For example, in one embodiment, the central server 120 sends an email to the fleet management system user indicating that engine idle data having an abnormal duration has been detected. In a further embodiment, the email may display the particular data having an abnormal duration or provide a link to the data. In yet another embodiment, the central server 120 may generate an alert via a user interface (e.g., the user interface shown in FIG. 10) indicating the identified engine idle segments. Next, at step 516, the central server 120 stores, in the system's memory, all of the data generated by the central server 120 in steps 506 through 514 (e.g., vehicle segment determinations, alert identifiers).

Steps 520 through 534 show an exemplary set of logic used by the central server to call various modules configured to conduct more detailed analyses of the telematics data received and processed in steps 506 through 514. As described above, according to certain embodiments, the fleet management system 5 may include a user interface through which a user of the system 5 may interact with the system and make choices. For example, the user interface may provide the user with options to (i) view potential inefficiencies indicated by the telematics data, (ii) view potential safety hazards indicated by the telematics data, (iii) view potential theft hazards indicated by the telematics data, and (iv) view more travel analysis options.

At step 520, the central server 120 determines whether a user of the fleet management system 5 has requested that the system 5 identify potential inefficiencies in a driver's delivery process indicated by the telematics data. If the user has requested this option, the central server 120 moves to step 522, where it calls the Efficiency analysis module 600. If the user has not requested this option, the central server 120 moves to step 524.

At step 524, the central server 120 determines whether a user of the fleet management system 5 has requested that the system 5 identify potential safety hazards in a driver's delivery process indicated by the telematics data. If the user has requested this option, the central server 120 moves to step 526, where it calls the Safety analysis module 700. If the user has not requested this option, the central server 120 moves to step 528.

At step 528, the central server 120 determines whether a user of the fleet management system 5 has requested that the system 5 identify potential theft hazards in a driver's delivery process indicated by the telematics data. If the user has requested this option, the central server 120 moves to step 530, where it calls the Theft analysis module 800. If the user has not requested this option, the central server 120 moves to step 532.

At step 528, the central server 120 determines whether a user of the fleet management system 5 has requested to view additional travel analysis options (e.g., calculating engine idle time percentages and calculating travel delays). If the user has requested this option, the central server 120 moves to step 534, where it calls the Travel analysis module 800. If the user has not requested this option, the central server 120 loops back to step 502.

In other embodiments, the central server may be configured not to execute steps 520, 524, 528, and 532. For example, in one embodiment, the central server is configured to automatically execute steps 522, 526, 530 and 534. In addition, according to other embodiments, the central server 120 may be configured to execute all or a portion of the steps illustrated in FIG. 5 in the same or a different order.

Efficiency Analysis Module

According to various embodiments, the efficiency analysis module 600 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential inefficient operation of a delivery vehicle and (ii) identify specific inefficient operations indicated by the engine idle segments and associated telematics data.

FIG. 6 illustrates exemplary steps executed by the efficiency analysis module 600 according to one embodiment. Beginning with step 602, the efficiency analysis module 600 receives user preferences for an efficiency analysis in the form of analysis parameters. For example, in one embodiment, a user may specify one or more of the following parameters in order to narrow the telematics data analyzed by the efficiency analysis module 600: (1) date; (2) time; (3) vehicle (e.g., a vehicle number); (4) driver (e.g., name or employee id); (5) route (e.g., route number); (6) vehicle trip segment (e.g., Start of Trip); and (7) vehicle event (e.g., seat belt engaged or disengaged). For each parameter, the user may specify a particular value (e.g., a date), range of values (e.g., range of dates), or series of values (e.g., two or more non-consecutive dates) defining the telematics data to be used by efficiency analysis module 600. Parameters without a specified value or values are ignored by the efficiency analysis module 600.

Next, at step 603, the efficiency analysis module 600 retrieves telematics data stored by the central server 120 meeting the analysis parameters received in step 602. This may be accomplished by using the analysis parameters as a filter for retrieving the telematics data. For example, if a user specifies a particular date, route number, and vehicle trip segment, the efficiency analysis module 600 will retrieve all telematics data captured on the specified date, for vehicles traveling along the specified route, and during the specified vehicle trip segment. In one embodiment, the desired telematics data is identified by using the contextual metadata associated with the stored telematics data by the telematics device 102 (see FIG. 4, step 410).

Next, at step 604, the efficiency analysis module 600 identifies all engine idle segments present in the retrieved telematics data having an alert identifier assigned by the central server 120 (see FIG. 5, step 512). As described above, in one embodiment, engine idle segments having been determined to have an abnormal duration are assigned an alert identifier by the central server 120.

Next, at step 606, the efficiency analysis module 600 displays the identified abnormal engine idle segments via a user interface. This allows the user to view all engine idle segments having an abnormal idle duration that meet the initial analysis parameters. According to one embodiment, these idle segments may be displayed in a table, similar to that illustrated in FIG. 10, showing the date and time each idle segment was captured, the vehicle trip segment during which each engine idle segment occurred, and the duration of each engine idle segment. In a further embodiment, the table may be configured such that the user may select a particular engine idle segment (e.g., with a computer mouse) and view the telematics data collected proximately before, proximately after, or during the particular engine idle segment. In this embodiment, the user has the option of browsing the telematics data captured during or proximate to the engine idle segment to determine the source of any potential inefficiencies.

Next, at step 608, the efficiency analysis module 600 determines whether the user has requested the central server 120 to identify potential inefficiencies indicated by the identified engine idle segments and retrieved telematics data (e.g., by selecting this option with a computer mouse via a user interface). If the user has not made this request, the efficiency analysis module 600 moves to step 614. If the user has made this request, the efficiency analysis module 600 moves to step 610.

Next, at step 610, the efficiency analysis module 600 identifies the retrieved engine idle segments meeting one or more sets of defined inefficiency criteria. According to one embodiment, the inefficiency criteria are programmable criteria for identifying specific potential inefficiencies in a delivery process. For example, a common inefficient operation in a delivery process occurs when a driver starts a delivery vehicle and allows the vehicle to idle while he or she fastens the vehicle's driver's side seat belt. By not fastening the seat belt before starting the vehicle's engine, the driver allows the vehicle to unnecessarily idle for a short period of time, wasting fuel and unnecessarily increasing the wear on the vehicle's engine. To identify the occurrence of this particular inefficient operation from the engine idle segments and telematics data, inefficiency criteria may be defined and associated with the inefficient operation.

For example, in one embodiment, inefficiency criteria associated with the operation of allowing the vehicle to idle while securing a seat belt is defined as any engine idle segment occurring in the start of trip segment where the telematics data indicates a seat belt was secured during the engine idle segment. In this embodiment, to determine whether any engine idle segments meet this inefficiency criteria, the efficiency analysis module 600 first identifies, from the set of previously identified engine idle segments meeting the analysis parameters, the engine idle segments occurring in the start of trip segment. For each of these start of trip engine idle segments, the efficiency analysis module 600 determines the duration of the engine idle segment and the time the engine idle segment began (or ended). Using the duration and start or end time as a guide, the efficiency analysis module 600 then searches the telematics data collected and stored during each engine idle segment for data indicating a seat belt was engaged. If the telematics data indicates a seat belt was engaged during a particular engine idle segment, the efficiency analysis module 600 determines that this particular inefficient operation (i.e., allowing the vehicle to idle while securing a seat belt) occurred for the vehicle, driver, and route associated with the particular engine idle segment.

According to various embodiments, the efficiency analysis module 600 may be configured to identify additional or different inefficient operations based on defined inefficiency criteria for each inefficient operation. Exemplary inefficient operations identifiable by the efficiency analysis module 600 include but are not limited to: (1) allowing a vehicle to idle while disengaging a seat belt; (2) allowing the vehicle to idle while opening or closing the bulkhead door (or other door) of the vehicle; and (3) allowing the vehicle to idle while using a portable data acquisition device (e.g., a DIAD). Inefficiency criteria may be defined and identified for these and other inefficient operations by the efficiency analysis module 600 in a manner similar to that described above.

Next, at step 612, the efficiency analysis module 600 displays information via a user interface indicating the specific inefficient operations determined to have occurred in step 610. In one embodiment, step 612 may also include displaying or providing a link to the specific telematics data indicating an identified inefficient operation.

Next, at step 614, the efficiency analysis module 600 calculates the actual engine idle time for the analysis parameters. For example, if a user specifies a particular date and vehicle in the analysis parameters, the efficiency analysis module 600 will calculate the actual engine idle time for the specified vehicle on the specified date. In one embodiment, the actual engine idle time represents the total amount of time a vehicle's (or vehicles′) engine was idling for a period specified by the analysis parameters. In the example above, the actual engine idle time would represent the total amount of time the specified vehicle's engine was idling for the entire specified day.

According to one embodiment, the efficiency analysis module 600 is configured to determine the actual engine idle time for a set of analysis parameters by first identifying the engine idle segments meeting the analysis parameters and then calculating the total combined duration of all identified engine idle segments. This may be accomplished, for example, by retrieving all of the engine idle segments present in the telematics data retrieved in step 603 (e.g., the engine idle segments meeting the analysis parameters), adding the durations of all engine idle segments, and returning the calculated value.

For the purposes of evaluating the efficiency of operations, however, the actual engine idle time for a set of analysis parameters may in some instances be misleading. For example, certain significant amounts of engine idle time may be attributable to events which are not the result of a driver's inefficiency, such as travel delays. Accordingly, to better identify the engine idle time associated with driver inefficiencies, the efficiency analysis module 600 is further configured at step 616 to calculate the corrected engine idle time for the analysis parameters. In one embodiment, the corrected engine idle time represents the actual engine idle time less any engine idle time attributable to travel delays.

According to one embodiment, the efficiency analysis module 600 is configured to determine the corrected engine idle time by first identifying, from the engine idle segments used to calculate the actual engine idle time, those engine idle segments caused by travel delays. For example, in one embodiment, the efficiency analysis module 600 may accomplish this by identifying the engine idle segments associated with during travel vehicle trip segments. Next, the efficiency analysis module 600 examines the telematics data captured during those engine idle segments and searches for data indicating non-travel related delays. For example, in one embodiment, the efficiency analysis module 600 is configured such that if the telematics data captured during a during travel engine idle segment indicates that the vehicle's parking brake was engaged during the engine idle segment, the engine idle segment will not be associated with a travel delay. In further embodiments, the efficiency analysis module 600 may be configured to identify other data indicating non-travel related delays, such as a seat belt being disengaged during the engine idle segment.

By examining the telematics data captured during each identified engine idle segment, the efficiency analysis module 600 isolates those engine idle segments attributable to travel delays. The efficiency analysis module 600 is configured to then add the duration of each engine idle segment attributable to travel delays to calculate the total amount of engine idle time associated with travel delays for the analysis parameters. Finally, the efficiency analysis module 600 calculates the corrected engine idle time by subtracting the total amount of engine idle time associated with travel delays from the actual engine idle time determined in step 614.

Next, at step 618, the efficiency analysis module displays the calculated actual engine idle time and corrected engine idle time. According to the other embodiments, the efficiency analysis module 600 may be configured to display only one of these calculated values based on user preferences. For example, in the exemplary user interface shown in FIG. 10, the actual engine idle time is labeled as “Total Idle Time Mins” in the left column.

Next, at step 620, the efficiency analysis module 600 calculates the actual engine idle time percentage. In one embodiment, this is accomplished by determining from the telematics data the total engine running time for the analysis parameters and dividing the actual engine idle time calculated in step 614 by the total engine running time. The resulting actual engine idle time percentage represents the percentage of total engine running time the vehicle engine was idling.

Next, at step 622, the efficiency analysis module 600 calculates the corrected engine idle time percentage. In one embodiment, this is accomplished by dividing the corrected engine idle time calculated in step 616 by the total engine running time. The resulting corrected engine idle time percentage represents the percentage of total engine running time the vehicles' engine was idling due to non-travel delays.

Next, at step 624, the efficiency analysis module 600 displays the calculated actual engine idle time percentage and calculated corrected engine idle time percentage via a user interface. According to the other embodiments, the efficiency analysis module 600 may be configured to display only one of these calculated values based on user preferences. For example, FIG. 10 shows an exemplary user interface configured to display, among other things, engine idle segments that the central server 120 has associated with vehicle trip segments and the engine idle time percentage calculated from those engine idle segments. The actual engine idle time percentage is labeled as “Idle % of Total Engine Runtime.” In addition, the exemplary user interface includes a table of engine idle segments. For each engine idle segment, the table displays the start time of the segment (the “Start” column), the vehicle trip segment in which the engine idle segment occurred (the “Idle Type” column), and the duration of the engine idle segment (the “Idle Time” column).

According to another embodiment (not shown), the efficiency analysis module 600 is further configured to generate an alert indicating to a user of the fleet management system 5 that a potential driver inefficiency has been detected. For example, in one embodiment, the central server 120 sends an email to the fleet management system user indicating that a potential driver inefficiency has been detected and describing the potential driver inefficiency. In a further embodiment, the email may display the particular telematics data indicating the driver inefficiency or provide a link to the data. In yet another embodiment, the central server 120 generates an alert via a user interface (e.g., the user interface shown in FIG. 10) indicating the identified engine idle segments.

According to further embodiments (not show), the efficiency analysis module 600 is configured to compare efficiency statistics (e.g., engine idle time percentage) for different analysis parameters. For example, in one embodiment, the travel analysis module 900 is configured to compare engine idle time percentage associated with different drivers on a particular date. In FIG. 10, the central server 120 has calculated efficiency statistics for each of the drivers listed in the top right box. By selecting a driver, “John Doe” in the Figure, a user can view statistics for that driver. According to other embodiments, the efficiency analysis module 900 is configured to display the results in a comparative format.

According to other embodiments, the efficiency analysis module 600 may be configured to execute all or a portion of the steps shown in FIG. 6 in the same or a different order. For example, in one embodiment, the efficiency analysis module does not execute step 608 and, instead, executes steps 610 and 612 automatically without providing a user with the option detected in step 608. In yet another embodiment, additional steps may be added to the efficiency analysis module 600 to make steps 614-624 optional steps executed in response to a user request.

Safety Analysis Module

According to various embodiments, the safety analysis module 700 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential safety hazards present in the operation of a delivery vehicle and (ii) identify specific safety hazards indicated by the engine idle segments and associated telematics data.

FIG. 7 illustrates exemplary steps executed by the safety analysis module 700 according to one embodiment. Beginning with step 702, the safety analysis module 700 receives user preferences for a safety analysis in the form of analysis parameters. These analysis parameters may be, for example, the same or similar to those described above in relation to the efficiency analysis module 600. According to one embodiment, the safety analysis module 700 provides the user with the option of using analysis parameters previously specified for an efficiency analysis, or inputting unique parameters for the safety analysis.

Next, at step 703, the safety analysis module 700 retrieves telematics data stored by the central server 120 meeting the analysis parameters received in step 702. This may be accomplished, for example, in the same or a similar manner to that described above in relation to step 603 of the efficiency analysis module 600.

Next, at step 704, the safety analysis module 700 identifies all engine idle segments present in the retrieved telematics data having an alert identifier assigned by the central server 120 (see FIG. 5, step 512). Next, at step 706, the safety analysis module 700 displays the identified engine idle segments via a user interface. According to various embodiments, the identified engine idle segments may be displayed in any of the ways described above in relation to step 606 of the efficiency analysis module 600.

Next, at step 708, the safety analysis module 700 determines whether the user has requested the central server 120 to identify potential safety hazards indicated by the identified engine idle segments and retrieved telematics data (e.g., by selecting this option with a computer mouse via a user interface). If the user has not made this request, the safety analysis module 700 moves to step 709 and ends. If the user has made this request, the safety analysis module 700 moves to step 710.

Next, at step 710, the safety analysis module 700 identifies the retrieved engine idle segments meeting one or more sets of defined safety criteria. According to one embodiment, the safety criteria are programmable criteria for identifying specific potential safety hazards in a delivery process. For example, a common safety hazard in a delivery process occurs when a driver starts a delivery vehicle before fastening his or her seat belt. To identify the occurrence of this safety hazard from the engine idle segments and telematics data, safety criteria may be defined and associated with this particular safety hazard.

For example, in one embodiment, safety criteria associated with the starting a vehicle before fastening the seat belt is defined as any engine idle segment occurring in the start of trip segment where the telematics data indicates a seat belt was secured during the engine idle segment. In this embodiment, to determine whether any engine idle segments meet this safety criteria, the safety analysis module 700 first identifies, from the set of previously identified engine idle segments meeting the analysis parameters, the engine idle segments occurring in the start of trip segment. For each of these start of trip engine idle segments, the safety analysis module 700 determines the duration of the engine idle segment and the time the engine idle segment began (or ended). Using the duration and start or end time as a guide, the safety analysis module 700 then searches the telematics data collected and stored during each engine idle segment for data indicating a seat belt was engaged. If the telematics data indicates a seat belt was engaged during a particular engine idle segment, the safety analysis module 700 determines that this particular safety hazard (i.e., starting the vehicle without first securing a seat belt) occurred for the vehicle, driver, and route associated with the particular engine idle segment.

According to various embodiments, the safety analysis module 700 may be configured to identify additional or different safety hazards based on defined safety criteria for each safety hazard. Exemplary safety hazards identifiable by the safety analysis module 700 include but are not limited to the driver: (1) driving a vehicle with the seatbelt unsecured; (2) starting or driving a vehicle with the bulkhead door (or other door) open; (3) allowing the vehicle to idle while the driver is outside of the cockpit (which may be detected by having a sensor sense the driver grasping a handle to exit the vehicle while the vehicle is idling); and (4) driving the vehicle while using a portable data acquisition device (e.g., a DIAD). Safety criteria may be defined and identified for these and other safety hazards by the safety analysis module 700 in a manner similar to that described above.

Next, at step 712, the safety analysis module 700 displays information via a user interface indicating the specific safety hazards determined to have occurred in step 710. In one embodiment, step 712 may also include displaying or providing a link to the specific telematics data indicating an identified safety hazard.

According to another embodiment (not shown), the safety analysis module 700 is further configured to generate an alert indicating to a user of the fleet management system 5 that a potential safety hazard has been detected. For example, in one embodiment, the central server 120 sends an email to the fleet management system user indicating that a potential safety hazard has been detected and describing the potential safety hazard. In a further embodiment, the email may display the particular telematics data indicating the safety hazard or provide a link to the data. In yet another embodiment, the central server 120 generates an alert via a user interface (e.g., the user interface shown in FIG. 10) indicating the identified engine idle segments.

Theft Analysis Module

According to various embodiments, the theft analysis module 800 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) identify engine idle segments indicating potential theft hazards present in the operation of a delivery vehicle and (ii) identify specific theft hazards indicated by the engine idle segments and associated telematics data.

FIG. 8 illustrates exemplary steps executed by the theft analysis module 800 according to one embodiment. Beginning with step 802, the theft analysis module 800 receives user preferences for a theft analysis in the form of analysis parameters. These analysis parameters may be, for example, the same or similar to those described above in relation to the efficiency analysis module 600 and safety analysis module 700. According to one embodiment, the theft analysis module 800 provides the user with the option of using analysis parameters previously specified for an efficiency analysis or safety analysis, or inputting unique parameters for the theft analysis.

Next, at step 803, the theft analysis module 800 retrieves telematics data stored by the central server 120 meeting the analysis parameters received in step 802. This may be accomplished, for example, in the same or a similar manner to that described above in relation to step 603 of the efficiency analysis module 600.

Next, at step 804, the theft analysis module 800 identifies all engine idle segments present in the retrieved telematics data having an alert identifier assigned by the central server 120 (see FIG. 5, step 512). Next, at step 806, the theft analysis module 800 displays the identified engine idle segments via a user interface. According to various embodiments, the identified engine idle segments may be displayed in any of the ways described above in relation to step 606 of the efficiency analysis module 600.

Next, at step 808, the theft analysis module 800 determines whether the user has requested the central server 120 to identify potential theft hazards indicated by the identified engine idle segments and retrieved telematics data (e.g., by selecting this option with a computer mouse via a user interface). If the user has not made this request, the theft analysis module 800 moves to step 809 and ends. If the user has made this request, the theft analysis module 800 moves to step 810.

Next, at step 810, the theft analysis module 800 identifies the retrieved engine idle segments meeting one or more sets of defined theft criteria. According to one embodiment, the theft criteria are programmable criteria for identifying specific potential theft hazards in a delivery process. For example, a common theft hazard in a delivery process occurs when a driver leaves a door to the delivery vehicle open while the engine is idling. To identify the occurrence of this theft hazard from the engine idle segments and telematics data, theft criteria may be defined and associated with this particular theft hazard.

For example, in one embodiment, theft criteria associated with leaving a door to the delivery vehicle open while the engine is idling is defined as any engine idle segment where the telematics data indicates a vehicle door is open during the engine idle segment. In this embodiment, to determine whether any engine idle segments meet this theft criteria, the theft analysis module 800 first retrieves the set of previously identified engine idle segments associated with alert identifiers. For each of these engine idle segments, the theft analysis module 800 determines the duration of the engine idle segment and the time the engine idle segment began (or ended). Using the duration and start or end time as a guide, the theft analysis module 800 then searches the telematics data collected and stored during each engine idle segment for data indicating a door to the vehicle was open. If the telematics data indicates a door to the vehicle was open during a particular engine idle segment, the theft analysis module 800 determines that this particular theft hazard (i.e., leaving a vehicle door open while the engine is idling) occurred for the vehicle, driver, and route associated with the particular engine idle segment.

According to various embodiments, the theft analysis module 800 may be configured to identify additional or different theft hazards based on defined theft criteria for each theft hazard. Exemplary theft hazards identifiable by the theft analysis module 800 include but are not limited to: (1) allowing the vehicle to idle while outside of the cockpit (e.g., sensing the driver grasp a handle to exit the vehicle while the vehicle is idling); and (2) failing to secure or lock vehicle doors. Theft criteria may be defined and identified for these and other theft hazards by the theft analysis module 800 in a manner similar to that described above.

Next, at step 812, the theft analysis module 800 displays information via a user interface indicating the specific theft hazards determined to have occurred in step 810. In one embodiment, step 812 may also include displaying or providing a link to the specific telematics data indicating an identified theft hazard.

According to another embodiment (not shown), the theft analysis module 800 is further configured to generate an alert indicating to a user of the fleet management system 5 that a potential theft hazard has been detected. For example, in one embodiment, the central server 120 sends an email to the fleet management system user indicating that a potential theft hazard has been detected and describing the potential theft hazard. In a further embodiment, the email may display the particular telematics data indicating the theft hazard or provide a link to the data. In yet another embodiment, the central server 120 generates an alert via a user interface (e.g., the user interface shown in FIG. 10) indicating the identified engine idle segments.

Travel Analysis Module

According to various embodiments, the travel analysis module 900 is configured to provide a user with various options for analyzing travel aspects of the delivery vehicles 100 in the fleet management system 5. In one embodiment, the travel analysis module 900 is configured to analyze engine idle data in relation to other telematics data and in accordance with user preferences to (i) estimate the travel delay associated with particular analysis parameters and (ii) determine the actual vehicle speed and corrected vehicle speed for vehicles associated with particular analysis parameters.

FIG. 9 illustrates exemplary steps executed by the travel analysis module 900 according to one embodiment. Beginning with step 902, the travel analysis module 900 receives user preferences for a travel analysis in the form of analysis parameters. These analysis parameters may be, for example, the same or similar to those described above in relation to the efficiency analysis module 600, safety analysis module 700, and theft analysis module 900. According to one embodiment, the travel analysis module 900 provides the user with the option of using analysis parameters previously specified for an efficiency analysis, safety analysis, or theft analysis, or inputting unique parameters for the travel analysis.

Next, at step 903, the travel analysis module 900 retrieves telematics data stored by the central server 120 meeting the analysis parameters received in step 902. This may be accomplished, for example, in the same or a similar manner to that described above in relation to step 603 of the efficiency analysis module 600.

Next, at step 904, the travel analysis module 900 identifies all engine idle segments present in the retrieved telematics data having an alert identifier assigned by the central server 120 (see FIG. 5, step 512). Next, at step 906, the travel analysis module 900 displays the identified engine idle segments via a user interface. According to various embodiments, the identified engine idle segments may be displayed in any of the ways described above in relation to step 606 of the efficiency analysis module 600.

Next, at step 908, the travel analysis module 900 determines whether the user has requested the central server 120 to estimate the travel delay time for vehicles and/or routes specified in the analysis parameters (e.g., by selecting this option with a computer mouse via a user interface). If the user has not made this request, the travel analysis module 900 moves to step 914. If the user has made this request, the travel analysis module 900 moves to step 910.

Next, at step 910, the travel analysis module 900 estimates the travel delay or delays associated with the specified analysis parameters. For example, if the user specifies a particular date and vehicle, the travel analysis module 900 will estimate the travel delay for the specified vehicle over the course of the specified date. If the user further specifies a particular route, the travel analysis module 900 will estimate the travel delay for the specified vehicle while traveling along the specified route on the specified date. As another example, if the user specifies only a date and route, the travel analysis module 900 will estimate the travel delay for each vehicle traveling along the specified route on the specified date.

According to one embodiment, the travel analysis module 900 is configured to estimate the travel delay for a particular vehicle by first identifying, from the engine idle segments identified in step 904, those engine idle segments caused by travel delays. This may be accomplished, for example, in the manner described above in relation to step 616 executed by the efficiency analysis module 600. Next, the travel analysis module 900 examines the telematics data captured during those engine idle segments and searches for data indicating non-travel related delays. This may also be accomplished, for example, in the manner described above in relation to step 616 executed by the efficiency analysis module 600.

By examining the telematics data captured during each identified engine idle segment, the travel analysis module 900 isolates those engine idle segments attributable to travel delays. The travel analysis module 900 is configured to then add the durations of each engine idle segment attributable to travel delays to calculate the total amount of engine idle time associated with travel delays for the analysis parameters. The engine idle time associated with travel delays serves as an estimate of the travel delay.

Next, at step 912, the travel analysis module 900 displays via a user interface the travel delay estimated in step 810. In one embodiment, step 912 may also include displaying or providing a link to the specific telematics data used to estimate the travel delay.

Next, at step 914, the travel analysis module 900 determines whether the user has requested the central server 120 to calculate vehicle speeds for vehicles specified in the analysis parameters (e.g., by selecting this option with a computer mouse via a user interface). If the user has not made this request, the travel analysis module 900 moves to step 915 and ends. If the user has made this request, the travel analysis module 900 moves to step 916.

Next, at step 916, the travel analysis module 900 calculates the actual vehicle speed for vehicles specified in the analysis parameters. As described above, the relevant vehicles may be defined by the analysis parameters in terms of specific vehicles, or vehicles associated with a specified route or routes. In addition, actual speed for the relevant vehicles will be calculated for the analysis parameters. For example, if the user specifies in the analysis parameters a particular vehicle, date, and route, the travel analysis module 900 will calculate the average actual speed of the specified vehicle while traveling on the specified route on the specified day. As another example, if the user specifies in the analysis parameters a particular vehicle, date, and two geographic points, the travel analysis module 900 will calculate the average actual speed of the specified vehicle while traveling between the two specified geographic points on the specified date. As yet another example, if the user specifies in the analysis parameters a particular route and a particular time period (e.g., 7:00 am to 9:00 am), the travel analysis module 900 will calculate the average actual speed of each vehicle traveling along the specified route during the specified time period on the specified date.

In various embodiments, the travel analysis module 900 is configured to calculate the actual vehicle speed for each relevant vehicle(s) by first determining, from the telematics data retrieved in step 903, the distance traveled by the relevant vehicle(s) according to the analysis parameters and the travel time for that that distance. Next, by dividing the distance traveled by the travel time, the travel analysis module 900 calculates the actual vehicle speed for the analysis parameters.

Next, at step 918, the travel analysis module 900 calculates the corrected vehicle speed for the relevant vehicles according to the analysis parameters. In one embodiment, the travel analysis module 900 is configured to calculate the corrected vehicle speed by first determining the travel delay time associated with the analysis parameters. This may be accomplished, for example, as described above in step 910. Next, the travel analysis module 900 subtracts the travel delay time from the travel time determined in step 916, resulting in a corrected travel time representing the actual travel time less time attributed to travel delays. Finally, by the distance traveled (calculated in step 916) by the corrected travel time, the travel analysis module 900 calculates the corrected vehicle speed for the analysis parameters.

According to further embodiments (not show), the travel analysis module 900 is configured to compare travel delay and vehicle speed figures calculated for different analysis parameters. For example, in one embodiment, the travel analysis module 900 is configured to compare travel delays associated with two different routes on a particular date. In this embodiment, the travel analysis module 900 is configured to calculate the travel delays for vehicles traveling on each route and display the results in a comparative format. Similarly, in other embodiments, the travel analysis module 900 is configured to compare vehicle speeds for various analysis parameters.

CONCLUSION

As should be appreciated, the embodiments may be implemented in various ways, including as methods, apparatus, systems, or computer program products. Accordingly, the embodiments may take the form of an entirely hardware embodiment or an embodiment in which a processor is programmed to perform certain steps. Furthermore, the various implementations may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions embodied in the storage medium. Any suitable computer-readable storage medium may be utilized including hard disks, CD-ROMs, optical storage devices, or magnetic storage devices.

The embodiments are described below with reference to block diagrams and flowchart illustrations of methods, apparatus, systems, and computer program products. It should be understood that each block of the block diagrams and flowchart illustrations, respectively, may be implemented in part by computer program instructions, e.g., as logical steps or operations executing on a processor in a computing system. These computer program instructions may be loaded onto a computer, such as a special purpose computer or other programmable data processing apparatus to produce a specifically-configured machine, such that the instructions which execute on the computer or other programmable data processing apparatus implement the functions specified in the flowchart block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including computer-readable instructions for implementing the functionality specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions that execute on the computer or other programmable apparatus provide operations for implementing the functions specified in the flowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrations support various combinations for performing the specified functions, combinations of operations for performing the specified functions and program instructions for performing the specified functions. It should also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.

Many modifications and other embodiments of the inventions set forth herein will come to mind to one skilled in the art to which these embodiments of the invention pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the embodiments of the invention are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation. 

What is claimed is:
 1. A fleet management system configured for managing a distributed network of fleet vehicles, the system comprising: a plurality of telematics devices with each of the respective telematics devices affixed to a corresponding fleet vehicle, wherein each telematics device is configured to: monitor a plurality of onboard sensors located on the corresponding fleet vehicle; and upon detecting one or more trigger events, record telematics data received from one or more of the onboard sensors, wherein the recorded telematics data is indicative of the corresponding vehicle's ignition status and the corresponding vehicle's engine speed; and a computer system comprising one or more memory storage areas and one or more processors, wherein the one or more processors are configured to: receive, from each of the plurality of telematics devices, recorded telematics data for each of the fleet vehicles; segment the recorded telematics data for each of the fleet vehicles into one or more vehicle trips, wherein each vehicle trip is defined by a period of time during which the corresponding vehicle's engine is continuously active, and each vehicle trip comprises one or more vehicle trip segments distinguished from other vehicle trip segments occurring within the same vehicle trip based on vehicle activity; associate at least one of the one or more trigger events with a vehicle trip segment; and determine, based at least in part on the association between the one or more trigger events and the vehicle trip segments, whether the one or more trigger events satisfy a predefined travel analysis criteria; and generate a graphical user display illustrating at least a portion of the recorded telematics data, wherein the graphical user display indicates whether the one or more trigger events satisfy a predefined travel analysis criteria.
 2. The fleet management system of claim 1, wherein the one or more trigger events comprise at least one of: a fleet vehicle engine turning on and beginning to idle; a fleet vehicle engine turning off; a fleet vehicle speed increasing from zero; a fleet vehicle speed decreasing to zero; a seat belt being engaged; a seat belt being disengaged; a fleet vehicle door opening; or a fleet vehicle door closing.
 3. The fleet management system of claim 1, wherein two temporally adjacent vehicle trip segments are distinguished based on the occurrence of a first trigger event.
 4. The fleet management system of claim 3, wherein determining whether the one or more trigger events satisfy a predefined travel analysis criteria comprises steps for determining whether a second trigger event occurs after the first trigger event.
 5. The fleet management system of claim 1, wherein the at least one of the plurality of telematics devices is configured to monitor a plurality of onboard sensors while the corresponding fleet vehicle's engine is turned off.
 6. The fleet management system of claim 1, wherein the travel analysis criteria is selected from: an efficiency criteria; a safety criteria; or a theft hazard criteria.
 7. The fleet management system of claim 1, wherein associating at least one of the one or more trigger events with a vehicle trip segment comprises associating the at least one of the one or more trigger events with a vehicle trip segment selected from the group consisting of: a start of trip segment; a during travel segment; and an end of trip segment.
 8. A method for managing a distributed network of fleet vehicles, the method comprising steps for: monitoring, via a plurality of telematics devices each affixed to a corresponding fleet vehicle, a plurality of onboard sensors located on each corresponding fleet vehicle; upon detecting one or more trigger events, recording, via at least one of the plurality of telematics devices, telematics data received from one or more of the onboard sensors, wherein the recorded telematics data is indicative of the corresponding fleet vehicle's ignition status and the corresponding fleet vehicle's engine speed; transmitting recorded telematics data from the at least one of the plurality of telematics devices to a central computing system; segmenting, via the central computing system, the recorded telematics data for each of the fleet vehicles into one or more vehicle trips, wherein each vehicle trip is defined by a period of time during which the corresponding fleet vehicle's engine is continuously active, and each vehicle trip comprises one or more vehicle trip segments distinguished from other vehicle trip segments occurring within the same vehicle trip based on vehicle activity; associating, via the central computing system, at least one of the one or more trigger events with a vehicle trip segment; determining, via the central computing system and based at least in part on the association between the one or more trigger events and the vehicle trip segments, whether the one or more trigger events satisfy a predefined travel analysis criteria; and generating, via the central computing system and a graphical display, a graphical user display illustrating at least a portion of the recorded telematics data, wherein the graphical user display indicates whether the one or more trigger events satisfy a predefined travel analysis criteria.
 9. The method of claim 8, wherein the one or more trigger events comprise at least one of: a fleet vehicle engine turning on and beginning to idle; a fleet vehicle engine turning off; a fleet vehicle speed increasing from zero; a fleet vehicle speed decreasing to zero; a seat belt being engaged; a seat belt being disengaged; a fleet vehicle door opening; or a fleet vehicle door closing.
 10. The method of claim 8, wherein two temporally adjacent vehicle trip segments are distinguished based on the occurrence of a first trigger event.
 11. The method of claim 10, wherein determining whether the one or more trigger events satisfy a predefined travel analysis criteria comprises steps for determining whether a second trigger event occurs after the first trigger event.
 12. The method of claim 8, wherein the at least one telematics device is configured to monitor a plurality of onboard sensors while the corresponding fleet vehicle's engine is turned off.
 13. The method of claim 8, wherein the travel analysis criteria is selected from: an efficiency criteria; a safety criteria; or a theft hazard criteria.
 14. The method of claim 8, wherein associating at least one of the one or more trigger events with a vehicle trip segment comprises associating the at least one of the one or more trigger events with a vehicle trip segment selected from the group consisting of: a start of trip segment; a during travel segment; and an end of trip segment.
 15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: an executable portion configured to receive, from a plurality telematics devices, telematics data for each of a plurality of fleet vehicles, wherein the telematics data is recorded by telematics devices each affixed to a corresponding fleet vehicle upon detection of one or more trigger events and the telematics data is indicative of the corresponding fleet vehicle's ignition status and the corresponding fleet vehicle's engine speed; an executable portion configured to segment the recorded telematics data for each of the fleet vehicles into one or more vehicle trips, wherein each vehicle trip is defined by a period of time during which the corresponding fleet vehicle's engine is continuously active, and each vehicle trip comprises one or more vehicle trip segments distinguished from other vehicle trip segments occurring within the same vehicle trip based on vehicle activity; an executable portion configured to associate at least one of the one or more trigger events with a vehicle trip segment; and an executable portion configured to determine, based at least in part on the association between the one or more trigger events and the vehicle trip segments, whether the one or more trigger events satisfy a predefined travel analysis criteria; and an executable portion configured to generate a graphical user display illustrating at least a portion of the recorded telematics data, wherein the graphical user display indicates whether the one or more trigger events satisfy a predefined travel analysis criteria.
 16. The computer program product of claim 15, wherein the one or more trigger events comprise at least one of: a fleet vehicle engine turning on and beginning to idle; a fleet vehicle engine turning off; a fleet vehicle speed increasing from zero; a fleet vehicle speed decreasing to zero; a seat belt being engaged; a seat belt being disengaged; a fleet vehicle door opening; or a fleet vehicle door closing.
 17. The computer program product of claim 15, wherein two temporally adjacent vehicle trip segments are distinguished based on the occurrence of a first trigger event.
 18. The computer program product of claim 17, wherein determining whether the one or more trigger events satisfy a predefined travel analysis criteria comprises steps for determining whether a second trigger event occurs after the first trigger event.
 19. The computer program product of claim 15, wherein the travel analysis criteria is selected from: an efficiency criteria; a safety criteria; or a theft hazard criteria.
 20. The computer program product of claim 15, wherein associating at least one of the one or more trigger events with a vehicle trip segment comprises associating the at least one of the one or more trigger events with a vehicle trip segment selected from the group consisting of: a start of trip segment; a during travel segment; and an end of trip segment. 